Candice A. Myers

The geographic concentration of US adult obesity prevalence and associated social, economic, and environmental factors.

This study used spatial statistical methods to test the hypotheses that county‐level adult obesity prevalence in the United States is (1) regionally concentrated at significant levels, and (2) linked to local‐level factors, after controlling for state‐level effects.

Regional disparities in obesity prevalence in the United States: A spatial regime analysis

Significant clusters of high‐ and low‐obesity counties have been demonstrated across the United States (US). This study examined regional disparities in obesity prevalence and differences in the related structural characteristics across regions of the US.

Change in Obesity Prevalence across the United States Is Influenced by Recreational and Healthcare Contexts, Food Environments, and Hispanic Populations

Objective To examine change in county-level adult obesity prevalence between 2004 and 2009 and identify associated community characteristics. Methods Change in county-level adult (≥20 years) obesity prevalence was calculated for a 5-year period (2004–2009). Community measures of economic, healthcare, recreational, food environment, population structure, and education contexts were also calculated. Regression analysis was used to assess community characteristics associated (p<0.01) with change in adult obesity prevalence. Results Mean±SD change in obesity prevalence was 5.1±2.4%. Obesity prevalence decreased in 1.4% (n = 44) and increased in 98% (n = 3,060) of counties from 2004–2009. Results showed that both baseline levels and increases in physically inactive adults were associated with greater increases in obesity prevalence, while baseline levels of and increases in physician density and grocery store/supercenter density were related to smaller increases in obesity rates. Baseline levels of the Hispanic population share were negatively linked to changing obesity levels, while places with greater Hispanic population growth saw greater increases in obesity. Conclusions Most counties in the U.S. experienced increases in adult obesity prevalence from 2004 to 2009. Findings suggest that community-based interventions targeting adult obesity need to incorporate a range of community factors, such as levels of physical inactivity, access to physicians, availability of food outlets, and ethnic/racial population composition.

Smartloss: A Personalized Mobile Health Intervention for Weight Management and Health Promotion

Background Synonymous with increased use of mobile phones has been the development of mobile health (mHealth) technology for improving health, including weight management. Behavior change theory (eg, the theory of planned behavior) can be effectively encapsulated into mobile phone-based health improvement programs, which is fostered by the ability of mobile phones and related devices to collect and transmit objective data in near real time and for health care or research professionals and clients to communicate easily. Objective To describe SmartLoss, a semiautomated mHealth platform for weight loss. Methods We developed and validated a dynamic energy balance model that determines the amount of weight an individual will lose over time if they are adherent to an energy intake prescription. This model was incorporated into computer code that enables adherence to a prescribed caloric prescription determined from the change in body weight of the individual. Data from the individual are then used to guide personalized recommendations regarding weight loss and behavior change via a semiautomated mHealth platform called SmartLoss, which consists of 2 elements: (1) a clinician dashboard and (2) a mobile phone app. SmartLoss includes and interfaces with a network-connected bathroom scale and a Bluetooth-connected accelerometer, which enables automated collection of client information (eg, body weight change and physical activity patterns), as well as the systematic delivery of preplanned health materials and automated feedback that is based on client data and is designed to foster prolonged adherence with body weight, diet, and exercise goals. The clinician dashboard allows for efficient remote monitoring of all clients simultaneously, which may further increase adherence, personalization of treatment, treatment fidelity, and efficacy. Results Evidence of the efficacy of the SmartLoss approach has been reported previously. The present report provides a thorough description of the SmartLoss Virtual Weight Management Suite, a professionally programmed platform that facilitates treatment fidelity and the ability to customize interventions and disseminate them widely. Conclusions SmartLoss functions as a virtual weight management clinic that relies upon empirical weight loss research and behavioral theory to promote behavior change and weight loss.

Diabetes prevalence is associated with different community factors in the diabetes belt versus the rest of the United States

To investigate differences in community characteristics associated with diabetes prevalence between the Diabetes Belt and the rest of the contiguous United States (U.S.)

Validity of the Remote Food Photography Method Against Doubly Labeled Water Among Minority Preschoolers

The aim of this study was to determine the validity of energy intake (EI) estimations made using the remote food photography method (RFPM) compared to the doubly labeled water (DLW) method in minority preschool children in a free‐living environment.

The Influence of Neighborhood Crime on Increases in Physical Activity during a Pilot Physical Activity Intervention in Children

The purpose of this study was to examine whether neighborhood crime moderated the response (increases in steps) to a pilot intervention to increase physical activity in children. Twenty-seven insufficiently active children aged 6–10 years (mean age = 8.7 years; 56 % female; 59 % African American) were randomly assigned to an intensive intervention group (IIG) or minimal intervention group (MIG). Change in average daily number of steps from baseline was regressed against an index of neighborhood crime in a multilevel repeated-measures model that included a propensity score to reduce confounding. Safer neighborhoods were associated with higher increases in steps during the pilot intervention (interaction p = 0.008). Children in the IIG living in low-crime neighborhoods significantly increased their physical activity (5275 ± 1040 steps/day) while those living in high-crime neighborhoods did not (1118 ± 1007) (p for difference = 0.046). In the IIG, the increase in daily steps was highly correlated with neighborhood crime (r = 0.58, p = 0.04). These findings suggest the need for physical activity interventions to account for participants’ environments in their design and/or delivery. To promote healthy behaviors in less-supportive environments, future studies should seek to understand how environments modify intervention response and to identify mediators of the relationship between environment and intervention.

Frequency of Consuming Foods Predicts Changes in Cravings for Those Foods During Weight Loss: The POUNDS Lost Study

Food cravings are thought to be the result of conditioning or pairing hunger with consumption of certain foods.

Examination of the reliability and validity of the Mindful Eating Questionnaire in pregnant women

OBJECTIVE Mindfulness is theorized to affect the eating behavior and weight of pregnant women, yet no measure has been validated during pregnancy. METHODS This study qualitatively and quantitatively evaluated the reliability and validity of the Mindful Eating Questionnaire (MEQ) in overweight and obese pregnant women. Participants completed focus groups and cognitive interviews. The MEQ was administered twice to measure test-retest reliability. The Eating Inventory (EI) and Mindful Attention Awareness Scale (MAAS) were administered to assess convergent validity, and the Neighborhood Environment Walkability Scale (NEWS) assessed discriminant validity. RESULTS Participants were 20 ± 8 weeks gestation (mean ± SD), 30 ± 2 years old, and 55% were obese. The MEQ total score had good test-retest reliability (r = .85). The total score internal consistency reliability was poor (Cronbachs α = .56). The external cues subscale (ECS) was not internally consistent (α = .31). Other subscales ranged from α = .59-.68. When the ECS was excluded, the MEQ total score internal consistency was acceptable (α = .62). Convergent validity was supported by the MEQ total score (with and without ECS) correlating significantly with the MAAS and the EI disinhibition and hunger subscales. Discriminant validity of the MEQ was supported by the MEQ and NEWS total scores and subscales not being significantly correlated. The quantitative results were supported by the qualitative context and content analysis. CONCLUSION With the exception of the ECS, the MEQs reliability and validity was supported in pregnant women, and most of the subscales were more robust in pregnant women than in the original sample of healthy adults. The MEQs use with overweight and obese pregnant women is supported.

Reliability and Validity of a Novel Internet-Based Battery to Assess Mood and Cognitive Function in the Elderly

Dementia is a chronic condition in the elderly and depression is often a concurrent symptom. As populations continue to age, accessible and useful tools to screen for cognitive function and its associated symptoms in elderly populations are needed. The aim of this study was to test the reliability and validity of a new internet-based assessment battery for screening mood and cognitive function in an elderly population. Specifically, the Helping Hand Technology (HHT) assessments for depression (HHT-D) and global cognitive function (HHT-G) were evaluated in a sample of 57 elderly participants (22 male, 35 female) aged 59-85 years. The study sample was categorized into three groups: 1) dementia (n = 8; Mini-Mental State Exam (MMSE) score 10-24), 2) mild cognitive impairment (n = 24; MMSE score 25-28), and 3) control (n = 25; MMSE score 29-30). Test-retest reliability (Pearson correlation coefficient, r) and internal consistency reliability (Cronbachs alpha, α) of the HHT-D and HHT-G were assessed. Validity of the HHT-D and HHT-G was tested via comparison (Pearson r) to commonly used pencil-and-paper based assessments: HHT-D versus the Geriatric Depression Scale (GDS) and HHT-G versus the MMSE. Good test-retest (r = 0.80; p < 0.0001) and acceptable internal consistency reliability (α= 0.73) of the HHT-D were established. Moderate support for the validity of the HHT-D was obtained (r = 0.60 between the HHT-D and GDS; p < 0.0001). Results indicated good test-retest (r = 0.87; p < 0.0001) and acceptable internal consistency reliability (α= 0.70) of the HHT-G. Validity of the HHT-G was supported (r = 0.71 between the HHT-G and MMSE; p < 0.0001). In summary, the HHT-D and HHT-G were found to be reliable and valid computerized assessments to screen for depression and cognitive status, respectively, in an elderly sample.